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I nterfacing the MORPC Regional Model with Dynamic Traffic Simulation David Roden (AECOM) Supin Yoder (FHWA) Nick Gill and Zhuojun Jiang (MORPC) Rebekah Anderson and Greg Giaimo (ODOT). FHWA – TRANSIMS Deployment Project. Agenda. Study Overview Network Conversion and Debugging

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FHWA – TRANSIMS Deployment Project

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Interfacing the MORPC Regional Model with Dynamic Traffic SimulationDavid Roden (AECOM)Supin Yoder (FHWA)Nick Gill and Zhuojun Jiang (MORPC)Rebekah Anderson and Greg Giaimo (ODOT)

FHWA – TRANSIMS Deployment Project


  • Study Overview

  • Network Conversion and Debugging

  • Trip and/or Tour Conversion

  • User Equilibrium Assignment and Convergence

  • Output Results and Sensitivity Tests

MORPC TRANSIMS Implementation

Purpose of the Study

  • AECOM, MORPC, ODOT, and FHWA are participating in a study to route and simulate MORPC’s tour-based demand on a TRANSIMS network

    • Create a time-dependent TRANSIMS network

    • Route and simulate TP+ trips on the TRANSIMS network

    • Route and simulate MORPC tours on the TRANSIMS network

    • Feedback travel times from TRANSIMS to the tour model

    • Create a time-dependent transit network and tour routing

MORPC TRANSIMS Implementation

Network Conversion Process

MORPC TRANSIMS Implementation


MORPC TRANSIMS Implementation

TRANSIMS Coding Concepts

MORPC TRANSIMS Implementation

Original/Default TRANSIMS Network

MORPC TRANSIMS Implementation

Zone Connector Activity Locations

MORPC TRANSIMS Implementation

Freeway Access Problems

Loop ramps were added to the TP+ network to improve results

MORPC TRANSIMS Implementation

TRANSIMS Travel Demand Concepts

  • TRANSIMS models individual persons for 24+ hours

  • Trips between specific activity locations, at specific times of day, using a specific travel mode and vehicle

    • Activity locations – street locations / block faces

    • Time of day (start/end/duration) – seconds

    • Modes – walk, bike, drive, ride, transit, P&R, K&R, etc.

  • Convert aggregate trip tables to individual travelers at specific locations and trip start times

    • Zones  activity locations within the zone

    • Daily/time period  second of the day

MORPC TRANSIMS Implementation

Trip Table Conversion Process

Block Boundaries

Block Data


Traffic Counts

Zone Boundaries

MORPC Zone Data

Non-HH Trip Tables

MORPC Diurnals

Subzone Factors


TP+ Scripts


Activity Location

Activity Location

Trip Tables

Diurnal Distributions


Trip File

Vehicle File

Household File

Population File

MORPC TRANSIMS Implementation

Diurnal Smoothing Results

MORPC TRANSIMS Implementation

Activity Location Weights

  • Use subzone socio-economic data to calculate trip attraction weights by trip purpose and orientation for each activity location within a TAZ

  • MORPC/ODOT provided a block data file to calculate the attraction weights

  • Inconsistencies between the TAZ and block file boundaries and socio-economic attributes necessitated complex data processing

MORPC TRANSIMS Implementation

TAZ – Block Data Integration Issues

MORPC TRANSIMS Implementation


Activities have


start times

and durations

Trips connect


MORPC TRANSIMS Implementation

TRANSIMS Router and Microsimulator

  • Router builds a unique path for each trip

    • Between origin and destination activity locations (link-offset)

    • Starting at a specific second of the day

    • Using a specified travel mode and vehicle

    • Based on network travel times in15-minute increments

  • Microsimulator moves vehicles between link-lane-cells on a second-by-second basis

    • Cells are 6 meters long

    • Vehicles move 0, 1, 2, 3, 4, 5, or 6 cells each second

      • Speeds = 0, 13.5, 27.0, 40.5, 54.0, 67.5 or 81.0 mph

MORPC TRANSIMS Implementation

Microsimulator Feedback Loops

Trips / Tours



Travel Paths








Travel Times


MORPC TRANSIMS Implementation

Convergence Statistics

  • Convergence is defined using multiple statistics

    • Simulation stability and network performance

      • Number and location of “lost” vehicles by time of day

      • Difference between the average link delay and the Microsimulator link delay – vehicle hours of travel by link and time of day

    • User Equilibrium – no traveler can improve their travel time (impedance) by changing paths

      • Difference between the simulated path and the minimum impedance path for each traveler – vehicle hours of travel by trip

      • The percentage of travelers with significant differences

MORPC TRANSIMS Implementation

Lost Vehicle Problems

Iteration 1

Iteration 25

MORPC TRANSIMS Implementation

Trip-Model Convergence Statistics

MORPC TRANSIMS Implementation

Trip Gap by Time of Day

MORPC TRANSIMS Implementation

Link VHT Gap by Time of Day

MORPC TRANSIMS Implementation

ATR 601: I-70 at Brice Rd.

MORPC TRANSIMS Implementation

Total Volume: All Stations

MORPC TRANSIMS Implementation

Operational Impact Test

  • Used the turning movement volumes from the simulation to update the signal timing plans for all signals in the region

  • Applied Progression to calculate signal offsets

  • Applied Router-Microsimulator to convergence

MORPC TRANSIMS Implementation

Signal Timing and Progression

Aggregate Wait Time Problems

Signal Progression Corridors

MORPC TRANSIMS Implementation

Daily Cycle Failures – Original

MORPC TRANSIMS Implementation

Daily Cycle Failures – Operational Test

MORPC TRANSIMS Implementation

Next Steps

  • Implement global iterations between the tour-model and the network simulation

  • Perform sensitivity tests and future forecasts

  • Refine operational details in downtown to provide demand data for a VISSIM subarea analysis

  • Upgrade the model to TRANSIMS Version 5 Studio and Visualizer

MORPC TRANSIMS Implementation

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